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Option data and modeling BSM implied volatility

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  • Matthias Fengler

Abstract

This contribution to the Handbook of Computational Finance, Springer-Verlag, gives an overview on modeling implied volatility data. After introducing the concept of Black-Scholes-Merton implied volatility (IV), the empirical stylized facts of IV data are reviewed. We then discuss recent results on IV surface dynamics and the computational aspects of IV. The main focus is on various parametric, semi- and nonparametric modeling strategies for IV data, including ones which respect no-arbitrage bounds.

Suggested Citation

  • Matthias Fengler, 2010. "Option data and modeling BSM implied volatility," University of St. Gallen Department of Economics working paper series 2010 2010-32, Department of Economics, University of St. Gallen.
    • Handle: RePEc:usg:dp2010:2010-32
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    File URL: http://ux-tauri.unisg.ch/RePEc/usg/dp2010/DP-1032-Fe.pdf
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    References listed on IDEAS

    as
    1. Mark Britten‐Jones & Anthony Neuberger, 2000. "Option Prices, Implied Price Processes, and Stochastic Volatility," Journal of Finance, American Finance Association, vol. 55(2), pages 839-866, April.
    2. repec:bla:jfinan:v:58:y:2003:i:2:p:753-778 is not listed on IDEAS
    3. Steven P. Feinstein, 1988. "A source of unbiased implied volatility forecasts," FRB Atlanta Working Paper 88-9, Federal Reserve Bank of Atlanta.
    4. Rama Cont & Jose da Fonseca, 2002. "Dynamics of implied volatility surfaces," Quantitative Finance, Taylor & Francis Journals, vol. 2(1), pages 45-60.
    5. Peter Carr & Liuren Wu, 2003. "The Finite Moment Log Stable Process and Option Pricing," Journal of Finance, American Finance Association, vol. 58(2), pages 753-777, April.
    6. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    7. repec:bla:jfinan:v:53:y:1998:i:6:p:2059-2106 is not listed on IDEAS
    8. Corrado, Charles J. & Miller, Thomas Jr., 1996. "A note on a simple, accurate formula to compute implied standard deviations," Journal of Banking & Finance, Elsevier, vol. 20(3), pages 595-603, April.
    9. M. Benko & M. Fengler & W. Härdle & M. Kopa, 2007. "On extracting information implied in options," Computational Statistics, Springer, vol. 22(4), pages 543-553, December.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Cristian Homescu, 2011. "Implied Volatility Surface: Construction Methodologies and Characteristics," Papers 1107.1834, arXiv.org.
    2. Noshaba Zulfiqar & Saqib Gulzar, 2021. "Implied volatility estimation of bitcoin options and the stylized facts of option pricing," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
    3. Gentle, James E. & Härdle, Wolfgang Karl, 2010. "Modeling asset prices," SFB 649 Discussion Papers 2010-031, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    4. Wolfgang Karl Härdle & Yarema Okhrin & Weining Wang, 2015. "Uniform Confidence Bands for Pricing Kernels," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 376-413.
    5. repec:hum:wpaper:sfb649dp2010-003 is not listed on IDEAS
    6. Bo Zhao & Stewart Hodges, 2013. "Parametric modeling of implied smile functions: a generalized SVI model," Review of Derivatives Research, Springer, vol. 16(1), pages 53-77, April.

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    More about this item

    Keywords

    Implied volatility;

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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